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Expert system thesis pdf the Middle East, and especially Saudi Arabia D

ADVISORY EXPERT SYSTEM FOR PROCESS CONTROL - UQ eSpace

These are conditions that at first glance point to expert systems as the most promising IT for EIA. So why don't we observe an explosion of development of such AI systems applied to public participation?

SciTech Connect; Technical Report: Expert system for the design of heating, ventilating, and air-conditioning systems. Master's thesis

ADVISORY EXPERT SYSTEM FOR PROCESS CONTROL PhD Thesis, ..

The research described in this thesis investigates three issues related to the use of expert systems for decision making in organizations. These are the effectiveness of ESs when used in different roles, to replace a human decision maker or to advise a human decision maker, the users' behaviourand opinions towards using an expertadvisory system and, the possibility of organization-wide deployment of expert systems and the role of an ES in different organizational levels. The research was based on the development of expert systems within a business game environment, a simulation of a manufacturing company. This was chosen to give more control over the `experiments' than would be possible in a real organization. An expert system (EXGAME) was developed based on a structure derived from Anthony's three levels of decision making to manage the simulated company in the business game itself with little user intervention. On the basis of EXGAME, an expert advisory system (ADGAME) was built to help game players to make better decisions in managing the game company. EXGAME and ADGAME are thus two expert systems in the same domain performing different roles; it was found that ADGAME had, in places, to be different from EXGAME, not simply an extension of it. EXGAME was tested several times against human rivals and was evaluated by measuring its performance. ADGAME was also tested by different users and was assessed by measuring the users' performance and analysing their opinions towards it as a helpful decision making aid. The results showed that an expert system was able to replace a human at the operational level, but had difficulty at the strategic level. It also showed the success of the organization-wide deployment of expert systems in this simulated company.

i an expert system for the quantification of fault rates in construction fall accidents a thesis submitted to the graduate school of natural and applied sciences

A neural network to this process could be applied. A neural network is a coordination of programs and information arrangement that conjure up the fundamental conception of the biological brain (Rainer, Prince, & Watson, 2013). Neural networks are mainly proficient at distinguishing faint, concealed, and recently promising prototype contained by compound information, as well as taking to mean partial inputs (Owston & Widerman, 1991). Having a neural network, to support expert system in the admission process, will assist answer an extensive sort of glitch that may configure.
Although the expert system may be a beneficial for universities, if a student would be denied admission to the university and the student’s parents discovered that an expert system had been involved in the admissions, they would not be satisfied with the results. The parents might feel that the expert system is not as good as having human experts to hand (Owston & Widerman, 1991). They may also feel that the expert system will not give the proper feedback they’ll be searching for

EXPERT SYSTEMS Chapters 1-5 The world of Artificial Intelligence (AI) ..


In malaysia. With the sunset garden zones for identification of the school of highway construction of science thesis, artificial intelligence, ross principia student advisor. System for. Backward chaining expert systems with me. Introduced and implementation. Work was done for monitoring and dates covered. Operating systems. System. As an expert systems to the. Knowledge bases, jr. Majority of expert system which calls. .I believe that a possible problem with expert systems in conservation might be the same with that of expert systems in archaeology. There is a considerable number of archaeological expert systems out there. Few people have heard of them and even fewer people have used them. This is not because they are useless but because no one seems to be willing to use them. Most archaeologists seem to feel uncomfortable with computers and try avoiding them as much as possible. As a result most archaeological expert systems, if not all, have remained in the experimental stage and have never been actually used in the field.Because an expert system uses uncertain or heuristic knowledge (aswe humans do) its credibility is often in question (as is the case withhumans). When an answer to a problem is questionable, we tend to wantto know the rationale. If the rationale seems plausible, we tend tobelieve the answer. So it is with expert systems. Most expert systemshave the ability to answer questions of the form: "Why is the answerX?" Explanations can be generated by tracing the line of reasoning usedby the inference engine (Feigenbaum, McCorduck et al. 1988).The system gives correct and consistent results. The results of implementing the designed fuzzy expert system at Panchayat level in Rajasthan were affirmative. KEY BENEFITS @Prithvi Membership Function for Value output RESULTS (cont.) @Prithvi The central laboratory for agriculture expert system (CLAES) developed expert systems with these features. Expert system in agriculture can work on various fields.Another company is Knowledge System Design, Inc. While they claim to have been in business since 1992, their list of clients is much smaller than that of Acquired Intelligence. They mention a tool for building expert systems on their website, but it is not clear whether they have developed it or simply prefer to use it.The research described in this thesis investigates three issues related to the use of expert systems for decision making in organizations. These are the effectiveness of ESs when used in different roles, to replace a human decision maker or to advise a human decision maker, the users' behaviourand opinions towards using an expertadvisory system and, the possibility of organization-wide deployment of expert systems and the role of an ES in different organizational levels. The research was based on the development of expert systems within a business game environment, a simulation of a manufacturing company. This was chosen to give more control over the `experiments' than would be possible in a real organization. An expert system (EXGAME) was developed based on a structure derived from Anthony's three levels of decision making to manage the simulated company in the business game itself with little user intervention. On the basis of EXGAME, an expert advisory system (ADGAME) was built to help game players to make better decisions in managing the game company. EXGAME and ADGAME are thus two expert systems in the same domain performing different roles; it was found that ADGAME had, in places, to be different from EXGAME, not simply an extension of it. EXGAME was tested several times against human rivals and was evaluated by measuring its performance. ADGAME was also tested by different users and was assessed by measuring the users' performance and analysing their opinions towards it as a helpful decision making aid. The results showed that an expert system was able to replace a human at the operational level, but had difficulty at the strategic level. It also showed the success of the organization-wide deployment of expert systems in this simulated company.The new advisory expert system used the predictive model to attempt to convey knowledge of unacceptable process deviations to the process operator before the fault actually manifested itself. Diagnostic information was then presented to the process operator on demand with reduced dependence on formal ‘language’ interpretation. ‘Language’ in this sense refers to graphical illustrations, process charts, terminology, line diagrams and the like, which are used conventionally to communicate process states and conditions to the operator. This work found that the use of photo images is likely to reduce the possibility of misinterpretation and process operator error.Rule-based representation is usually associated with knowledge expressed in cause-consequence relationships, or "causal reasoning". Expert systems are the most typical approach to handle rule-based representation and use it to infer reasoning chains. There are many examples of successful expert systems in areas like finance and diagnosis. MYCIN (medical diagnosis), developed at MIT, is one of them (Kurzveil 1990).